Senior Data Architect

Requirements

• Experience in automotive, service contracts, or lifecycle management domains
• Experience working in large enterprise environments
• What's in it for you?
• Ready for the next move?
• Sanjeet Kumar Jha,
• Email: sanjeet.kumar.jha@volvo.com
• Swedish Union representatives:Akademikerna - Mikael Johansson, +46 73 902 34 30Unionen - Lajla Dahlsjö, +46 31 322 45 75Ledarna - Carina Sachade, +46 73 902 40 83
• We value your data privacy and therefore do not accept applications via mail.
• Who we are and what we believe in

Additional Information

Company description: . Job description: This will be us - your new colleagues We're seeking a skilled Data Architect who can seamlessly connect business objectives with technical solutions and implementation. If you excel at tackling complexity, enjoy creating scalable architectures, and are eager to work with cutting-edge technologies, this role is for you. Your future team You will be part of a high performing team of skilled data professionals, such as Data Architects, Data Engineers, ML engineers & Data Analysts. You will closely collaborate with Digital Product Managers and Owners from Volvo Trucks. This role is based in Göteborg, Sweden, and requires you to work on-site at our office. What you will be doing? Design and implement scalable end-to-end data architecture on Azure and Databricks, aligned with enterprise standards. Define data models and enforce data standards, governance, and best practices across teams. Establish strong data governance, security, and compliance frameworks (RBAC, GDPR, lineage). Lead integration of operational systems, analytics platforms, and AI/ML use cases, including MLOps lifecycle support. Translate business needs into technical architecture, roadmaps, and key design decisions, including trade-off analysis. Provide technical leadership and mentorship, setting coding, engineering, and MLOps best practices while actively contributing hands-on. Who are you? Required Qualifications: Proven experience in designing and implementing data architectures on Azure and Databricks Strong expertise in data modeling across complex enterprise domains Deep understanding of: Data lifecycle and lineage Experience with system integration, APIs, and distributed architectures Data governance, security, and compliance Good understanding of MLOps and ML lifecycle management Strong software engineering fundamentals

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